BC3. Basque centre for climate change – Klima aldaketa ikergai

Objective 5: Integrated modelling of coupled human-natural systems

BC3 has a strong focus on methodological innovations in the field of informatics for sustainability. One example is the ARIES (ARtificial Intelligence for Ecosystem Services) project (http://aries.integratedmodelling.org), a highly recognized, pioneering example of an e-science collaboratory where independent actors can develop and share interoperable data and models. ARIES is the most well-known application of the semantically integrated modeling technology designed and developed at BC3, whose scope extends far beyond the current applications. The BC3 team, along with many International partners, has focused on the modeling of ecosystem services to provide a view of coupled human-natural systems that has been widely recognized in science, management and governance. Objective 5 describes the activities related to the modeling of socio-environmental systems; the activities that will support the more widespread application and maintenance of the integrated modeling technology are described separately as Strategic Project 2.


Activity 5.1. Scaled complexity in biophysical and social modeling.

The technology underlying ARIES can choose and assemble the most appropriate data and model components according to scale, detail, and availability of data. In data-poor contexts, the system adopts Bayesian belief network models that approximate the likely outcomes of physical processes through causal paths and correlations learned from data in comparable contexts. When data is available, the system adopts spatially explicit dynamic models of different processes. This scaled complexity approach allows best response and explicit communication of uncertainty in diverse contexts. (Lead: F. Villa)

Activity 5.2. Bridging disciplines: from biophysical to social through agriculture and food security.

The investigation on social agents is synergic with many integrated scenarios developed in other outcomes. In order to link data and models produced by other communities (such as agricultural, hydrological, pedological and geological) ARIES uses an approach driven by ontologies that reuses endorsed vocabularies and terminologies from recognized institutions and allows artifacts (such as data) of diverse provenance to be used jointly within integrated models. Negotiate effective translation of terminologies and continued interoperability is a crucial prerequisite to developing any effective trans-disciplinary project. (Lead: F. Villa)

Activity 5.3. Bridging scales: from process detail and agent behavior to economic and policy instruments.

Focusing on both, the biophysical mechanisms of ecosystem service provision, the socioeconomic drivers of their change and their implications for human well-being, requires integrating scales from local, through regional decision-making, to the country-level accounting of natural capital, which ultimately impacts the global economic system. Case studies for ARIES often cut across wide scale spans in space and time. Such activities have prompted the development of scale-aware methods and automatic scaling of models, with explicit account of the resulting uncertainties. Techniques such as Multiple Criteria Analysis have also been integrated into ARIES to provide rapid and easily communicable analysis and visualization of stakeholder priorities and potential conflicts over alternative goals at different scales. These instruments will allow the investigation of scaling trade-offs, such as those between short-term increase in provisioning services, and the long-term loss of regulating ones (e.g.  flood risk).  (Lead: S. Balbi)

Activity 5.4. Instrumenting decision makers.

Reconciling the need for simplicity and intuitiveness with that for accuracy, specificity and dynamic resolution is a challenge. By adapting models to diverse social, economic, and policy contexts without overly complicating their application by decision makers, ARIES opens the highly specialized practice of modelling to non-specialists, reduces its costs and potentially expands its role in decision making. ARIES can be used by decision makers to target economic incentives, while minimizing the information costs of identifying trade-offs between efficient and equitable targeting of ES providers. (Lead: F. Villa)


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